Abstract: Embodiments of the present invention recite a method of compiling color analysis parameters. In one embodiment of the present invention, a corrected color description of at least one test subject is constructed. The corrected color description of at least one test subject is then accessed. The at least one test subject is assigned to a classification color according the accessed corrected color description. The said classification color is then correlated with a prescriptive recommendation.

Abstract: Embodiments of the present invention recite a computer implemented method and system for estimating skin color from an image. In embodiments of the present invention, an image of a subject and of an imaged reference color set is accessed. In embodiments of the present invention, a controlled infrastructure is not required when capturing the image. At least one skin pixel of the subject is located in the image and a color description of the at least one skin pixel is determined. Then, a color correction function to be applied to the color description of the at least one skin pixel is determined. The color correction function is applied to the color description of the at least one skin pixel to create a modified color description. Finally, the skin color of the subject is estimated based upon an analysis of the modified color description.

Abstract: Embodiments of the present invention recite a computer implemented method for recommending a product based upon skin color estimated from a single captured image. In one embodiment of the present invention, a skin color estimate which is generated from a single captured image is accessed. The skin color estimate is then compared with a classification color. A correlation between the classification color and at least one product is accessed. Then, at least one of the products which corresponds with the classification color is recommended.

Abstract: Embodiments of the present invention recite a system and method for conveying the true color of a subject. In one embodiment, the present invention comprises an image capture device, an imaged reference color set comprising at least one reference color, and a control reference color set comprising at least one control color corresponding to the at least one reference color. The present invention further comprises a color correction component for accessing the control reference color set and the imaged reference color set and for generating a color correction function which eliminates a discrepancy between the at least one reference color and the at least one control color.

Abstract: Dense range data obtained at real-time rates is employed to estimate the pose of an articulated figure. In one approach, the range data is used in combination with a model of connected patches. Each patch is the planar convex hull of two circles, and a recursive procedure is carried out to determine an estimate of pose which most closely correlates to the range data. In another aspect of the invention, the dense range data is used in conjunction with image intensity information to improve pose tracking performance. The range information is used to determine the shape of an object, rather than assume a generic model or estimate structure from motion. In this aspect of the invention, a depth constraint equation, which is a counterpart to the classic brightness change constraint equation, is employed. Both constraints are used to jointly solve for motion estimates.

Abstract: Dense range data obtained at real-time rates is employed to estimate the pose of an articulated figure. In one approach, the range data is used in combination with a model of connected patches. Each patch is the planar convex hull of two circles, and a recursive procedure is carried out to determine an estimate of pose which most closely correlates to the range data. In another aspect of the invention, the dense range data is used in conjunction with image intensity information to improve pose tracking performance. The range information is used to determine the shape of an object, rather than assume a generic model or estimate structure from motion. In this aspect of the invention, a depth constraint equation, which is a counterpart to the classic brightness change constraint equation, is employed. Both constraints are used to jointly solve for motion estimates.

Abstract: Dense range data obtained at real-time rates is employed to estimate the pose of an articulated figure. In one approach, the range data is used in combination with a model of connected patches. Each patch is the planar convex hull of two circles, and a recursive procedure is carried out to determine an estimate of pose which most closely correlates to the range data. In another aspect of the invention, the dense range data is used in conjunction with image intensity information to improve pose tracking performance. The range information is used to determine the shape of an object, rather than assume a generic model or estimate structure from motion. In this aspect of the invention, a depth constraint equation, which is a counterpart to the classic brightness change constraint equation, is employed. Both constraints are used to jointly solve for motion estimates.

Abstract: A method for real-time video communication. Specifically, one embodiment of the present invention discloses a method of video conferencing that captures a plurality of real-time video streams of a local participant from a plurality of sample viewpoints. From the plurality of video streams, a new view synthesis technique can be applied to generate a video image stream in real-time of the local participant rendered from a second location of a second participant with respect to a first location of the local participant in a coordinate space of a virtual environment. A change in either of the locations leads to the modifying of the video image stream, thereby enabling real-time video communication from the local participant to the second participant.

Abstract: A method for real-time video communication. Specifically, one embodiment of the present invention discloses a method of video conferencing that captures a plurality of real-time video streams of a local participant from a plurality of sample viewpoints. From the plurality of video streams, a new view synthesis technique can be applied to generate a video image stream in real-time of the local participant rendered from a second location of a second participant with respect to a first location of the local participant in a coordinate space of a virtual environment. A change in either of the locations leads to the modifying of the video image stream, thereby enabling real-time video communication from the local participant to the second participant.

Abstract: A powerful, scaleable, and reconfigurable image processing system and method of processing data therein is described. This general purpose, reconfigurable engine with toroidal topology, distributed memory, and wide bandwidth I/O are capable of solving real applications at real-time speeds. The reconfigurable image processing system can be optimized to efficiently perform specialized computations, such as real-time video and audio processing. This reconfigurable image processing system provides high performance via high computational density, high memory bandwidth, and high I/O bandwidth. Generally, the reconfigurable image processing system and its control structure include a homogeneous array of 16 field programmable gate arrays (FPGA) and 16 static random access memories (SRAM) arranged in a partial torus configuration. The reconfigurable image processing system also includes a PCI bus interface chip, a clock control chip, and a datapath chip. It can be implemented in a single board.

Abstract: Techniques from computer vision and computer graphics are combined to robustly track a target (e.g., a user) and perform a function based upon the image and/or the identity attributed to the target's face. Three primary modules are used to track a user's head: depth estimation, color segmentation, and pattern classification. The combination of these three techniques allows for robust performance despite unknown background, crowded conditions, and rapidly changing pose or expression of the user. Each of the modules can also provide an identity classification module with valuable information so that the identity of a user can be estimated. With an estimate of the position of a target in 3-D and the target's identity, applications such as individualized computer programs or graphics techniques to distort and/or morph the shape or apparent material properties of the user's face can be performed.

Abstract: A powerful, scaleable, and reconfigurable image processing system and method of processing data therein is described. This general purpose, reconfigurable engine with toroidal topology, distributed memory, and wide bandwidth I/O are capable of solving real applications at real-time speeds. The reconfigurable image processing system can be optimized to efficiently perform specialized computations, such as real-time video and audio processing. This reconfigurable image processing system provides high performance via high computational density, high memory bandwidth, and high I/O bandwidth. Generally, the reconfigurable image processing system and its control structure include a homogeneous array of 16 field programmable gate arrays (FPGA) and 16 static random access memories (SRAM) arranged in a partial torus configuration. The reconfigurable image processing system also includes a PCI bus interface chip, a clock control chip, and a datapath chip. It can be implemented in a single board.

Abstract: Techniques from computer vision and computer graphics are combined to robustly track a target (e.g., a user) and perform a function based upon the image and/or the identity attributed to the target's face. Three primary modules are used to track a user's head: depth estimation, color segmentation, and pattern classification. The combination of these three techniques allows for robust performance despite unknown background, crowded conditions, and rapidly changing pose or expression of the user. Each of the modules can also provide an identity classification module with valuable information so that the identity of a user can be estimated. With an estimate of the position of a target in 3-D and the target's identity, applications such as individualized computer programs or graphics techniques to distort and/or morph the shape or apparent material properties of the user's face can be performed. The system can track and respond to a user's face in real-time using completely passive and non-invasive techniques.

Abstract: Techniques from computer vision and computer graphics are combined to robustly track a target (e.g., a user) and perform a function based upon the image and/or the identity attributed to the target's face. Three primary modules are used to track a user's head: depth estimation, color segmentation, and pattern classification. The combination of these three techniques allows for robust performance despite unknown background, crowded conditions, and rapidly changing pose or expression of the user. Each of the modules can also provide an identity classification module with valuable information so that the identity of a user can be estimated. With an estimate of the position of a target in 3-D and the target's identity, applications such as individualized computer programs or graphics techniques to distort and/or morph the shape or apparent material properties of the user's face can be performed.